DeepAI AI Chat
Log In Sign Up

Cribriform pattern detection in prostate histopathological images using deep learning models

by   Malay Singh, et al.

Architecture, size, and shape of glands are most important patterns used by pathologists for assessment of cancer malignancy in prostate histopathological tissue slides. Varying structures of glands along with cumbersome manual observations may result in subjective and inconsistent assessment. Cribriform gland with irregular border is an important feature in Gleason pattern 4. We propose using deep neural networks for cribriform pattern classification in prostate histopathological images. 163708 Hematoxylin and Eosin (H&E) stained images were extracted from histopathologic tissue slides of 19 patients with prostate cancer and annotated for cribriform patterns. Our automated image classification system analyses the H&E images to classify them as either `Cribriform' or `Non-cribriform'. Our system uses various deep learning approaches and hand-crafted image pixel intensity-based features. We present our results for cribriform pattern detection across various parameters and configuration allowed by our system. The combination of fine-tuned deep learning models outperformed the state-of-art nuclei feature based methods. Our image classification system achieved the testing accuracy of 85.93 ± 7.54 (cross-validated) and 88.04 ± 5.63 ( additional unseen test set) across three folds. In this paper, we present an annotated cribriform dataset along with analysis of deep learning models and hand-crafted features for cribriform pattern detection in prostate histopathological images.


page 4

page 6

page 10


Feasibility of Colon Cancer Detection in Confocal Laser Microscopy Images Using Convolution Neural Networks

Histological evaluation of tissue samples is a typical approach to ident...

A superpixel-driven deep learning approach for the analysis of dermatological wounds

Background. The image-based identification of distinct tissues within de...

Using Wavelets and Spectral Methods to Study Patterns in Image-Classification Datasets

Deep learning models extract, before a final classification layer, featu...

Giraffe: Using Deep Reinforcement Learning to Play Chess

This report presents Giraffe, a chess engine that uses self-play to disc...

Classification of histopathology images using ConvNets to detect Lupus Nephritis

Systemic lupus erythematosus (SLE) is an autoimmune disease in which the...